Accurately modeling how light interacts with cloth is challenging, due to the volumetric nature of cloth appearance and its multiscale structure, where microstructures play a major role in the overall appearance at higher scales. Recently, significant effort has been put on developing better microscopic models for cloth structure, which have allowed rendering fabrics with unprecedented fidelity. However, these highly-detailed representations still make severe simplifications on the scattering by individual fibers forming the cloth, ignoring the impact of fibers' shape, and avoiding to establish connections between the fibers' appearance and their optical and fabrication parameters. In this work we put our focus in the scattering of individual cloth fibers; we introduce a physically-based scattering model for fibers based on their low-level optical and geometric properties, relying on the extensive textile literature for accurate data. We demonstrate that scattering from cloth fibers exhibits much more complexity than current fiber models, showing important differences between cloth type, even in averaged conditions due to longer views. Our model can be plugged in any framework for cloth rendering, matches scattering measurements from real yarns, and is based on actual parameters used in the textile industry, allowing predictive bottom-up definition of cloth appearance.



@article{AliagaEGSR2017, author = {Aliaga, Carlos and Castillo, Carlos and Gutierrez, Diego and Otaduy, Miguel A. and Lopez-Moreno, Jorge and Jarabo, Adrian}, title = {An Appearance Model for Textile Fibers}, journal = {Computer Graphics Forum (Proc. EGSR 2017)}, year = {2017}, volume = {36}, number = {4} }


We want to thank Gabriel Cirio and Rosa Sánchez for the cloth models, Carlos Heras, Iñigo Salinas, and Ignacio Garcés for their help with the capturing setup, Miquel Rius from Gütermann for providing the real yarn samples and manufacturing details, and Julio Marco, Adolfo Muñoz, Sandra Malpica and Miguel Galindo for their help at different stages of the project. This research has been funded by the European Research Council (ERC Consolidator Grant, ref. 682080, and ERC Proof-of-Concept Grant, ref. 713742), DARPA (project REVEAL), and the Spanish Ministerio de Economía y Competitividad (projects TIN2016-78753-P, RTC2016-5122-5 and TIN2015-70799-R). C. Aliaga and J. Lopez-Moreno were additionally supported by a PhD grant from Gobierno de Aragón and a Juan de la Cierva fellowship, respectively.